Search Results for "linux os desktop"
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Showing 5 open source projects for "linux os desktop"
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Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Pixelyse
A simple tool for scanning and digitalizing your photos effortlessly.
Minimizes the number of steps required to perform scanning and photo extraction, making the process quicker and more efficient. A user-friendly interface and streamlined functionality allows you to go from document to extracted photos in just a few clicks. For more information and troubleshooting, check the readme file: https://sourceforge.net/p/pixelyse/code/ci/master/tree/README.md -
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ImaGC
image editor
an easy way to personalize images. -
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DreamStudio by Volocian Studios
Free yourself
Volocian believes first and foremost that financial status shouldn’t be a barrier to entry in multimedia content creation. Whether you want to design a product or website, record a band, remix a song, or produce a feature length movie with professional post production graphics and effects, Volocian™ wants to help, even if you’re using borrowed hardware with no previous experience. We provide affordable products and services for any budget, including cost-free solutions for education and demo... -
4
scrimage
A unique python-based image editor
A unique python-based image editor with low-level control. It will be able to apply fairly complex mathematical operations to individual pixels based on the contents of a script or user input at a command line. It will then be able to apply those changes to the image for a unique effect. -
Cloud data warehouse to power your data-driven innovationBigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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